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Updated: Jan 29, 2026

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在股票市场波动动态中量化泛同声事件的语言复杂性
Yunfan Zhang1, Jingqian Tian1,2, Yutong Zou1
1Department of FinTech, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Entropy (Basel, Switzerland)
|January 28, 2026
概括
泛同声事件是由类似的关键字和股票标记驱动的,导致股票价格波动. 这项研究表明,这些事件具有时间变化的影响,随着时间的推移,影响会减少.
科学领域:
- 行为金融是行为金融.
- 计算语言学 计算语言学
- 金融计量经济学 金融计量经济学
背景情况:
- 泛同音事件代表了一种新奇的现象,在这种现象中,语音相似性会影响股票市场的行为.
- 了解这些语言驱动的市场动态对于财务分析至关重要.
研究的目的:
- 调查泛同声事件对股票价格的影响,以楚安市为案例研究.
- 量化这些事件对市场波动的动态和时间变化的影响.
主要方法:
- 基于信息的语言振幅细分方法被用来分类事件强度.
- 关系式股票排名 (RSR) 模型和动态条件相关性-通用自行回归条件异构性 (DCC-GARCH) 框架被用于隔离特定事件的价格变化.
主要成果:
- 股票价格表现出一个连续反应,低幅度事件导致中度波动,高幅度事件导致显著波动.
- 价格的激增,通常在1-2天内发生,往往会在三周内恢复.
- 对泛同声刺激的重复暴露会导致市场反应减弱,这表明溢出效应正在减弱.
结论:
- 语言线索显著影响金融市场,影响股价动态.
- 该研究提供了对投资者行为,信息处理以及对此类事件的监管监督的需求的见解.
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